Uncertainty analysis and optimization of sinter cooling process for waste heat recovery

Tian, Wenya; Ni, Bingyu; Jiang, Chao; Wu, Zhonghua

doi:10.1016/j.applthermaleng.2018.12.162

Cited by 18 publications

(6 citation statements)

References 35 publications

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“…The relative error (RE) between the simulation results y(x) and the approximation of the neural network function f(x) can be expressed by Eq. ( 3 ) 48 …”

Section: Methodsmentioning

confidence: 99%

Uncertainty analysis and optimization of laser thermal pain treatment

Liu

She

Huang

et al. 2023

Sci Rep

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Uncertainty in operating parameters during laser thermal pain treatment can yield unreliable results. To ensure reliability and effectiveness, we performed uncertainty analysis and optimization on these parameters. Firstly, we conducted univariate analysis to identify significant operational parameters. Next, an agent model using RBNN regression determined the relationship between these parameters, the constraint function, and the target function. Using interval uncertainty analysis, we obtained confidence distributions and established a nonlinear interval optimization model. Introducing RPDI transformed the model into a deterministic optimization approach. Solving this with a genetic algorithm yielded an optimal solution. The results demonstrate that this solution significantly enhances treatment efficacy while ensuring temperature control stability and reliability. Accounting for parameter uncertainties is crucial for achieving dependable and effective laser thermal pain treatment. These findings have important implications for advancing the clinical application of this treatment and enhancing patient outcomes.

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“…The relative error (RE) between the simulation results y(x) and the approximation of the neural network function f(x) can be expressed by Eq. ( 3 ) 48 …”

Section: Methodsmentioning

confidence: 99%

Uncertainty analysis and optimization of laser thermal pain treatment

Liu

She

Huang

et al. 2023

Sci Rep

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“…The relative error between the simulation results y(x) and the approximation obtained by the regression function f(x) is written as Eq (7). [31].…”

Section: Rbnn Trainingmentioning

confidence: 99%

Uncertainty analysis and optimization for mild moxibustion

et al. 2023

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During mild moxibustion treatment, uncertainties are involved in the operating parameters, such as the moxa-burning temperature, the moxa stick sizes, the stick-to-skin distance, and the skin moisture content. It results in fluctuations in skin surface temperature during mild moxibustion. Existing mild moxibustion treatments almost ignore the uncertainty of operating parameters. The uncertainties lead to excessive skin surface temperature causing intense pain, or over-low temperature reducing efficacy. Therefore, the interval model was employed to measure the uncertainty of the operation parameters in mild moxibustion, and the uncertainty optimization design was performed for the operation parameters. It aimed to provide the maximum thermal penetration of mild moxibustion to enhance efficacy while meeting the surface temperature requirements. The interval uncertainty optimization can fully consider the operating parameter uncertainties to ensure optimal thermal penetration and avoid patient discomfort caused by excessive skin surface temperature. To reduce the computational burden of the optimization solution, a high-precision surrogate model was established through a radial basis neural network (RBNN), and a nonlinear interval model for mild moxibustion treatment was formulated. By introducing the reliability-based possibility degree of interval (RPDI), the interval uncertainty optimization was transformed into a deterministic optimization problem, solved by the genetic algorithm. The results showed that this method could significantly improve the thermal penetration of mild moxibustion while meeting the skin surface temperature requirements, thereby enhancing efficacy.

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“…Zhang 19 analyzed the influence of gas-to-material ratio and bed height on gas–solid heat transfer during the vertical cooling process by using a mathematical model of porous media heat transfer. Tian 20 conducted research on the optimization of operating parameters for the sintering cooler by establishing a three-dimensional flow and heat transfer calculation model, and established an analysis model 21 with the recovery rate of dust as the objective function to analyze and optimize the optimal operating parameters and structural parameters for sinter cooling.…”

Section: Introductionmentioning

confidence: 99%

Numerical study and orthogonal analysis of optimal performance parameters for vertical cooling of sintered ore

Wang,

Li,

Zhen

et al. 2024

Sci Rep

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The sinter cooler, essential for cooling hot sintered ore to a specific temperature, has seen recent advancements with the introduction of a vertical sinter cooling furnace. This innovation aims to enhance energy efficiency, reduce emissions, and improve waste heat recovery. Despite significant research, a quantitative analysis of factors impacting its cooling and heat transfer efficiency is lacking. This study utilizes the Euler model and local non-equilibrium thermodynamic theory to identify key factors affecting the gas–solid cooperative cooling process in the vertical cooler. Through an orthogonal experimental approach, the paper determines the optimal structural and operational parameters for the furnace. Key findings include that a gas–solid ratio of 1200m^3/t, inlet air temperature of 50 ℃, cooling section height of 6m, and diameter of 13.25m maximize efficiency, achieving a weighted range normalization value of 0.962. This configuration meets sintered ore cooling requirements while optimizing waste heat recovery. The study reveals that the impact on heat transfer efficiency is influenced primarily by the gas–solid ratio, followed by the cooling section's height, diameter, and inlet air temperature. These insights are crucial for enhancing the vertical sinter cooler's design, contributing to more energy-efficient and environmentally friendly sintering processes.

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Uncertainty analysis and optimization of sinter cooling process for waste heat recovery

Cited by 18 publications

References 35 publications

Uncertainty analysis and optimization of laser thermal pain treatment

Uncertainty analysis and optimization of laser thermal pain treatment

Uncertainty analysis and optimization for mild moxibustion

Numerical study and orthogonal analysis of optimal performance parameters for vertical cooling of sintered ore

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